The approaches described in this section are approaches that could be pursued, but not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section.
Computer-based database systems, such as relational database management systems, typically organize data according to a fixed structure of tables and relationships. The structure may be described using an ontology, embodied in a database schema, comprising a data model that is used to represent the structure and reason about objects in the structure.
An ontology of a database is normally fixed at the time that the database is created. Any change in the ontology represented by the schema is typically extremely disruptive to the database system and requires a database administrator to modify tables or relationships, or create new tables or relationships.
The rigidity of the typical database ontology is a serious drawback for organizations that require flexible and dynamic data processing techniques according to changes in the data that is collected. For example, intelligence analysis is poorly suited to conventional fixed ontology systems.